{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://matplotlib.org/api/_as_gen/matplotlib.pyplot.html#module-matplotlib.pyplot  \n",
    "plot(地基，基址图)  \n",
    "matplot(矩阵图)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`matplot.pyplot` is a state-based interface to matplotlib. It provides a MATLAB-like way of potting.  \n",
    "\n",
    "pyplot is mainly intended for interactive plots and smiple cases of programmatic plot generation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7c7c0b8>]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = np.arange(0,5,0.1)\n",
    "y = np.sin(x)\n",
    "plt.plot(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
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